{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4a801e3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>merchant_profit</th>\n",
       "      <th>customer_spending</th>\n",
       "      <th>customer_savings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>25.25</td>\n",
       "      <td>74.25</td>\n",
       "      <td>0.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>49.00</td>\n",
       "      <td>147.00</td>\n",
       "      <td>3.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>71.25</td>\n",
       "      <td>218.25</td>\n",
       "      <td>6.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>92.00</td>\n",
       "      <td>288.00</td>\n",
       "      <td>12.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>111.25</td>\n",
       "      <td>356.25</td>\n",
       "      <td>18.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>129.00</td>\n",
       "      <td>423.00</td>\n",
       "      <td>27.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>145.25</td>\n",
       "      <td>488.25</td>\n",
       "      <td>36.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>160.00</td>\n",
       "      <td>552.00</td>\n",
       "      <td>48.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>173.25</td>\n",
       "      <td>614.25</td>\n",
       "      <td>60.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>185.00</td>\n",
       "      <td>675.00</td>\n",
       "      <td>75.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>195.25</td>\n",
       "      <td>734.25</td>\n",
       "      <td>90.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>204.00</td>\n",
       "      <td>792.00</td>\n",
       "      <td>108.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>211.25</td>\n",
       "      <td>848.25</td>\n",
       "      <td>126.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>217.00</td>\n",
       "      <td>903.00</td>\n",
       "      <td>147.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>221.25</td>\n",
       "      <td>956.25</td>\n",
       "      <td>168.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>224.00</td>\n",
       "      <td>1008.00</td>\n",
       "      <td>192.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>225.25</td>\n",
       "      <td>1058.25</td>\n",
       "      <td>216.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>225.00</td>\n",
       "      <td>1107.00</td>\n",
       "      <td>243.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>223.25</td>\n",
       "      <td>1154.25</td>\n",
       "      <td>270.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>220.00</td>\n",
       "      <td>1200.00</td>\n",
       "      <td>300.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>215.25</td>\n",
       "      <td>1244.25</td>\n",
       "      <td>330.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>209.00</td>\n",
       "      <td>1287.00</td>\n",
       "      <td>363.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>201.25</td>\n",
       "      <td>1328.25</td>\n",
       "      <td>396.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>192.00</td>\n",
       "      <td>1368.00</td>\n",
       "      <td>432.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>181.25</td>\n",
       "      <td>1406.25</td>\n",
       "      <td>468.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>169.00</td>\n",
       "      <td>1443.00</td>\n",
       "      <td>507.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>155.25</td>\n",
       "      <td>1478.25</td>\n",
       "      <td>546.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>140.00</td>\n",
       "      <td>1512.00</td>\n",
       "      <td>588.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>123.25</td>\n",
       "      <td>1544.25</td>\n",
       "      <td>630.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>105.00</td>\n",
       "      <td>1575.00</td>\n",
       "      <td>675.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    num  merchant_profit  customer_spending  customer_savings\n",
       "0     1            25.25              74.25              0.75\n",
       "1     2            49.00             147.00              3.00\n",
       "2     3            71.25             218.25              6.75\n",
       "3     4            92.00             288.00             12.00\n",
       "4     5           111.25             356.25             18.75\n",
       "5     6           129.00             423.00             27.00\n",
       "6     7           145.25             488.25             36.75\n",
       "7     8           160.00             552.00             48.00\n",
       "8     9           173.25             614.25             60.75\n",
       "9    10           185.00             675.00             75.00\n",
       "10   11           195.25             734.25             90.75\n",
       "11   12           204.00             792.00            108.00\n",
       "12   13           211.25             848.25            126.75\n",
       "13   14           217.00             903.00            147.00\n",
       "14   15           221.25             956.25            168.75\n",
       "15   16           224.00            1008.00            192.00\n",
       "16   17           225.25            1058.25            216.75\n",
       "17   18           225.00            1107.00            243.00\n",
       "18   19           223.25            1154.25            270.75\n",
       "19   20           220.00            1200.00            300.00\n",
       "20   21           215.25            1244.25            330.75\n",
       "21   22           209.00            1287.00            363.00\n",
       "22   23           201.25            1328.25            396.75\n",
       "23   24           192.00            1368.00            432.00\n",
       "24   25           181.25            1406.25            468.75\n",
       "25   26           169.00            1443.00            507.00\n",
       "26   27           155.25            1478.25            546.75\n",
       "27   28           140.00            1512.00            588.00\n",
       "28   29           123.25            1544.25            630.75\n",
       "29   30           105.00            1575.00            675.00"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#自备数据源，读取操作\n",
    "#数据源 ./data1/data_sales.csv\n",
    "import pandas as pd\n",
    "data = pd.read_csv(\"./data1/data_sales.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7eb6665c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1\n",
       "1      2\n",
       "2      3\n",
       "3      4\n",
       "4      5\n",
       "5      6\n",
       "6      7\n",
       "7      8\n",
       "8      9\n",
       "9     10\n",
       "10    11\n",
       "11    12\n",
       "12    13\n",
       "13    14\n",
       "14    15\n",
       "15    16\n",
       "16    17\n",
       "17    18\n",
       "18    19\n",
       "19    20\n",
       "20    21\n",
       "21    22\n",
       "22    23\n",
       "23    24\n",
       "24    25\n",
       "25    26\n",
       "26    27\n",
       "27    28\n",
       "28    29\n",
       "29    30\n",
       "Name: num, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#顾客购买数量列表\n",
    "num_items = data['num']\n",
    "num_items"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "3e8f7e89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      25.25\n",
       "1      49.00\n",
       "2      71.25\n",
       "3      92.00\n",
       "4     111.25\n",
       "5     129.00\n",
       "6     145.25\n",
       "7     160.00\n",
       "8     173.25\n",
       "9     185.00\n",
       "10    195.25\n",
       "11    204.00\n",
       "12    211.25\n",
       "13    217.00\n",
       "14    221.25\n",
       "15    224.00\n",
       "16    225.25\n",
       "17    225.00\n",
       "18    223.25\n",
       "19    220.00\n",
       "20    215.25\n",
       "21    209.00\n",
       "22    201.25\n",
       "23    192.00\n",
       "24    181.25\n",
       "25    169.00\n",
       "26    155.25\n",
       "27    140.00\n",
       "28    123.25\n",
       "29    105.00\n",
       "Name: merchant_profit, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 商家收益列表\n",
    "merchant_profit = data['merchant_profit']\n",
    "merchant_profit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dbc9ef2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       74.25\n",
       "1      147.00\n",
       "2      218.25\n",
       "3      288.00\n",
       "4      356.25\n",
       "5      423.00\n",
       "6      488.25\n",
       "7      552.00\n",
       "8      614.25\n",
       "9      675.00\n",
       "10     734.25\n",
       "11     792.00\n",
       "12     848.25\n",
       "13     903.00\n",
       "14     956.25\n",
       "15    1008.00\n",
       "16    1058.25\n",
       "17    1107.00\n",
       "18    1154.25\n",
       "19    1200.00\n",
       "20    1244.25\n",
       "21    1287.00\n",
       "22    1328.25\n",
       "23    1368.00\n",
       "24    1406.25\n",
       "25    1443.00\n",
       "26    1478.25\n",
       "27    1512.00\n",
       "28    1544.25\n",
       "29    1575.00\n",
       "Name: customer_spending, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#顾客总消费列表\n",
    "customer_spending = data['customer_spending']\n",
    "customer_spending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0d029692",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0.75\n",
       "1       3.00\n",
       "2       6.75\n",
       "3      12.00\n",
       "4      18.75\n",
       "5      27.00\n",
       "6      36.75\n",
       "7      48.00\n",
       "8      60.75\n",
       "9      75.00\n",
       "10     90.75\n",
       "11    108.00\n",
       "12    126.75\n",
       "13    147.00\n",
       "14    168.75\n",
       "15    192.00\n",
       "16    216.75\n",
       "17    243.00\n",
       "18    270.75\n",
       "19    300.00\n",
       "20    330.75\n",
       "21    363.00\n",
       "22    396.75\n",
       "23    432.00\n",
       "24    468.75\n",
       "25    507.00\n",
       "26    546.75\n",
       "27    588.00\n",
       "28    630.75\n",
       "29    675.00\n",
       "Name: customer_savings, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#顾客省钱情况列表\n",
    "customer_savings = data['customer_savings']\n",
    "customer_savings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3e7c5a0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "#设置中文显示\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号\n",
    "\n",
    "#寻找商家收益最大的数量\n",
    "max_profit_num = num_items[list(merchant_profit).index(max(merchant_profit))]\n",
    "#最大利益\n",
    "max_profit = max(merchant_profit)\n",
    "\n",
    "#可视化数据\n",
    "plt.plot(num_items,merchant_profit,label='Merchant Profit',marker='o')\n",
    "plt.plot(num_items,customer_spending,label='Customer Spending',marker='o')\n",
    "plt.plot(num_items,customer_savings,label='Customer Saving',marker='o')\n",
    "\n",
    "#标记商场收益最大的批发数量和商场收益\n",
    "plt.annotate(f'Max Profit:{max_profit:.2f} at {max_profit_num} items',\n",
    "            xy=(max_profit_num,max_profit),\n",
    "            xytext=(max_profit_num-2,max_profit+600),\n",
    "            arrowprops=dict(facecolor='black',arrowstyle='->'))\n",
    "plt.xlabel(\"商家购买数量\")\n",
    "plt.ylabel(\"价格/元\")\n",
    "plt.title(\"\")\n",
    "plt.legend()\n",
    "# plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4fe874d4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
